Edge computing paradigm deploys infrastructures on users' edge side, enabling data to be stored in edge storage systems. Thus edge computing finds a balance between remote cloud storage with high latency and local storage with limited resources. However, the frequent update of edge data increases the probability of data corrupting. To ensure availability and integrity of edge data without affecting future use, this paper proposes a certificateLess edge recoverable data auditing (CL-ERDA) approach with corruption localization. First, the certificateless network coding signature in CL-ERDA is utilized to generate the homomorphic authenticator, addressing public key certificate management issues while avoiding insecure key escrow problems. Then, CL-ERDA designs a two-phase auditing method, where only file-level aggregation proofs are respond in first phase of external check and the second phase of self-check is launched only when damaged data is detected, reducing communication overhead of the auditing. Moreover, CL-ERDA combines hierarchical check method with batch localization method to achieve locating efficiently all the corrupted data at one time rather than locating only one corrupted data at once. Finally, security analysis shows that the proposed scheme resists various attacks and supports the unforgeability of authenticators. Experimental results demonstrate that CL-ERDA is efficient in auditing and corruption localization.

Object detection in autonomous driving benefits from federated learning (FL) for privacy, yet real deployments suffer from client heterogeneity and feature-dependent label noise, which hinder convergence and accuracy. We present FedPLC, a noise-robust FL framework with two synergistic components: (i) a candidate-box-aware progressive label correction (PLC) that performs confidence-gated, progressive pseudo-label updates at region level, and (ii) a performance-aware adaptive aggregation that re-weights client updates by validation performance, suppressing noisy clients. On UA-DETRAC with uniform, asymmetric, and feature-dependent noise at various ratios, FedPLC achieves higher mAP and more stable convergence than FedAvg and FL-OD, especially under high and feature-dependent noise.

Vehicular edge computing (VEC) leverages roadside units (RSUs) to provide low-latency and energy-efficient computation for vehicular networks. However, existing offloading schemes still face challenges under high vehicle mobility, dynamic network conditions, uneven RSUs loads, and different Quality of Service (QoS) requirements. To address this, we propose a mobility-aware partial task offloading (MAPRO) framework that partitions tasks for parallel processing across multiple RSUs while considering mobility, network dynamics, and QoS demands. A hybrid framework combining Proximal Policy Optimization (PPO) and numerical optimization efficiently solves offloading, resource allocation, and power control. Experiments on real trajectories show that MAPRO outperforms state-of-theart methods.

Real-time edge video analytics is essential for enabling effective decision support by offloading computation to edge servers. However, traditional methods suffer from limitations: transmission latency faces challenges under constrained network bandwidth, and adaptive configurations often inadequately consider the dynamic variations in video content. To this end, we propose a deep reinforcement learning based scenetarget fusion for content-aware adaptive configuration method (FCAC). Independent of preconceived assumptions about the environment, FCAC makes optimal choices based on experience. First, it extracts dynamic keyframes from original video frames. Then, it performs scene-target fusion to measure content features, obtaining factors affecting resolution, frame rate, and quantization. Finally, we implement and thoroughly evaluate the performance of FCAC in real-world network traces, the results on three real-world scenarios show the advantages of FCAC over state-of-the-art solutions.

Proofs of Retrievability (PoRs) and Provable Data Possession (PDP) are efficient cryptographic solutions to monitoring the state of storage, enabling integrity verification without the necessity of retrieving data. However, such protocols fail to guarantee data availability, since it is too late for cloud clients to recover the corrupted data when notified. To remedy it, these protocols are extended to verify integrity of both the stored data and their redundant copies in the multi-replica environment. Most of the existing multi-replica PDP protocols not only consume considerable computation and bandwidth resources of clients to generate and upload replicas, but also lead economic losses to service providers due to abused replica discounts. Though the other few considered these problems and proposed some countermeasures, they imposed the linear cost of generating and uploading copy parameters on clients in replication algorithms and fail to realize public verifiability. In this paper, we propose a public proofs of data replication and retrievability protocol with user-friendly replication for the first time. One distinguishable property is the simultaneous achievement of user-friendly replication and public verifiability. Specifically, we design a novel replication algorithm, which imposes nearly no computation and a constant-size communication cost on clients. Subsequently, we employ non-interactive succinct proofs to make the verification public. Furthermore, we present a comprehensive analysis and extensive experiments to demonstrate the security and efficiency of the proposed protocol.

The rapid development of both hardware and software has promoted the popularization of various real-time applications like health monitoring and intrusion detection that are widely deployed in outsourcing scenarios, e.g., mobile edge computing and cloud computing. In these applications, end devices continuously generate unbounded sequences of data items at a fast rate, i.e., the so-called streaming data. Nevertheless, storing and processing massive amounts of streaming data poses a challenge for resources-restricted end devices. Although outsourcing data items to edge servers or cloud servers is an attractive solution to the above problem, it also brings a new challenge, i.e., how to guarantee the integrity of outsourced data, since streaming data applications are usually sensitive of both location and the corresponding context, and servers are not completely trusted. To this end, the primitive of verifiable data streaming (VDS) protocol was introduced to maintain outsourced streaming data, while preserving its integrity. However, existing VDS constructions mainly use the structure of Merkle hash tree, and inherently have logarithmic costs. Consequently, they are infeasible for real-time applications that are delay sensitive and generate unpredictable size of streaming data. In this paper, we optimize previous VDS protocols from the aspects of communication overhead and computation cost. Specifically, we adopt a technical route different from Merkle hash tree, i.e, combining the digital signature with the cryptographic accumulator. In our construction, we employ Boneh-Lynn-Shacham (BLS) signature to guarantee the integrity of the context and position of each outsourced data item, and adopt an RSA accumulator to invalidate the old signature after the corresponding data item was updated. This immediately yields an optimal VDS construction that has constant costs even under concurrent queries, which is more desirable for those resource-limited mobile devices. In addition, the aggregability of BLS signature makes our VDS construction capable of data auditing, which enables the user to remotely verify the integrity of outsourced streaming data. We provide a formal security proof of the proposed VDS construction under well-studied complexity assumptions in the random oracle model. As a proof-of-concept, we also implement our proposal, and conduct extensive experiments to demonstrate its practicability.

Cloud auditing enables the integrity verification of cloud data without the necessity of data retrieval, which significantly promotes the storage service of cloud computing. Auditing with ownership transfer is a variation where both cloud data and the tags for integrity verification can be transferred. In some scenarios, like joint-stock enterprise acquisition and electronic medical records migration, we argue that auditing and transferring data belonging to multiple owners are significantly important. However, to the best of our knowledge, there exists no such protocol in multi-ownership scenarios in the literature. In this paper, we propose a blockchain-based accountable auditing protocol with multi-ownership transfer for the first time. One distinguishable property is the simultaneous achievement of verifiability, accountability and multi-ownership transferability, merely with very little extra cost. Specifically, we construct a novel tag structure based on homomorphic authenticators and compact multi-signatures, enabling integrity verification and multi-ownership transfer. Subsequently, we record the information concerning data generation and ownership transfer on immutable blockchains to make these procedures accountable. Furthermore, we present a comprehensive analysis and extensive experiments to demonstrate the security and efficiency of the proposed protocol.

Blockchain technology has been highly praised for its immutability, attracting considerable attention in the academic and industrial community. However, since permanent storage in blockchains would result in copyright disputes and harmful information spreads, it is desired to equip blockchains with mutability nowadays for legal and moral duty restrictions. A redactable blockchain is a variation, which enables the editing of block objects without affecting other blocks in the blockchain. Most existing redactable blockchains can only support editing operations such as modification and deletion, rather than insertion. However, insertion is necessary for some scenarios, especially when patching codes are needed for smart contracts and mistaken deletions occur. In addition, we argue that the verifiability of blockchains is also significantly important, especially for the redactable ones, in which one block may have multiple versions. Hence, an efficient mechanism is required to invalidate history versions and incent distributed adoptions of editing operations. In this paper, we propose a verifiable and redactable blockchain with fully editing operations for the first time. One distinguishable property is the simultaneous achievement of fully editability of block objects and verifiability of blockchain state, with acceptable extra cost. Specifically, we construct the redactable blockchain based on a double trapdoor chameleon hash family, enabling computationally efficient and key-exposure resistant block editing. Additionally, we combine trapdoorless universal accumulators and the largest sequence number principle to make the blockchain state verifiable. Furthermore, we present a comprehensive analysis and extensive experiments to demonstrate the security and feasibility of the proposed redactable blockchain.

Nowadays, Software Defined Network (SDN) develops rapidly for its novel structure which separates the control plane and the data plane of network devices. Many researchers devoted themselves to the study of such a special network. However, some limitations restrict the development of SDN. On the one hand, the single controller in the conventional model bears all threats, and the corruption of it will result in network paralysis. On the other hand, the data will be increasing more in SDN switches in the data plane, while the storage space of these switches is limited. In order to solve the mentioned issues, we propose two corresponding protocols in this paper. Specifically, one is an anonymous protocol in the control plane, and the other is a verifiable outsourcing protocol in the data plane. The evaluation indicates that our protocol is correct, secure, and efficient.

Cyberspace has become the most popular carrier of information exchange in every corner of our life, which is beneficial for our life in almost all aspects. With the continuous development of science and technology, especially the quantum computer, cyberspace security has become the most critical problem for the Internet in near future. In this paper, we focus on analyzing characteristics of the quantum cryptography and exploring of the advantages of it in the future Internet. It is worth noting that we analyze the quantum key distribution (QKD) protocol in the noise-free channel. Moreover, in order to simulate real situations in the future Internet, we also search the QKD protocol in the noisy channel. The results reflect the unconditional security of quantum cryptography theoretically, which is suitable for the Internet as ever-increasing challenges are inevitable in the future.

With the rapid development of cloud computing, cloud storage has been accepted by an increasing number of organizations and individuals, therein serving as a convenient and on-demand outsourcing application. However, upon losing local control of data, it becomes an urgent need for users to verify whether cloud service providers have stored their data securely. Hence, many researchers have devoted themselves to the design of auditing protocols directed at outsourced data. In this paper, we propose an efficient public auditing protocol with global and sampling blockless verification as well as batch auditing, where data dynamics are substantially more efficiently supported than is the case with the state of the art. Note that, the novel dynamic structure in our protocol consists of a doubly linked info table and a location array. Moreover, with such a structure, computational and communication overheads can be reduced substantially. Security analysis indicates that our protocol can achieve the desired properties. Moreover, numerical analysis and real-world experimental results demonstrate that the proposed protocol achieves a given efficiency in practice.